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| Short-term Output Power Prediction of Photovoltaic Generation based on a Grey Dynamic BP Neural Network |
| Lou Baolei |
| State Grid of China Technology College, Ji’nan 250002 |
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Abstract In order to avoid the shortcomings of traditional BP neural network in predicting the short-term output power of photovoltaic generation, a prediction model based on a grey dynamic BP neural network was proposed and realized in this paper. The grey system theory was adopted to improve the factor set of traditional BP neural network, meanwhile the number of nodes of hidden layer in the BP neural network was adjusted dynamically. At the end the proposed model was used to predict the short-term output power in a real photovoltaic power station. The results show that the predicted results agree well with the measured results, which verifies the validity of the model.
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Published: 09 December 2015
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| Cite this article: |
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Lou Baolei. Short-term Output Power Prediction of Photovoltaic Generation based on a Grey Dynamic BP Neural Network[J]. Electrical Engineering, 2015, 16(12): 47-51.
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| URL: |
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http://dqjs.cesmedia.cn/EN/Y2015/V16/I12/47
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2015, Vol. 16 
